app.py

import gradio as gr
from transformers import FlaxAutoModel, AutoTokenizer

def load_model_and_tokenizer(model_name):
    model = FlaxAutoModel.from_pretrained(model_name)
    tokenizer = AutoTokenizer.from_pretrained(model_name)
    return model, tokenizer

def generate_image(model, tokenizer, prompt):
    # Process the input prompt and generate the output image using the model and tokenizer
    # ...
    # output_image = ... (your implementation here)
    return output_image

def infer(prompt):
    model_name = "Ryukijano/controlnet-fill-circle"
    model, tokenizer = load_model_and_tokenizer(model_name)
    output_image = generate_image(model, tokenizer, prompt)
    return output_image

iface = gr.Interface(
    fn=infer,
    inputs=["text"],
    outputs="image",
    title="ControlNet Fill Circle",
    description="This is a demo of ControlNet Fill Circle.",
    examples=[
        ["red circle with blue background"],
        ["cyan circle with brown floral background"]
    ],
    theme="gradio/soft",
)

iface.launch()